Vehicle Feature Usage Preference from Mobile App Behavior
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Solution Overview
Problem
Vehicles are equipped with redundant features that duplicate functionalities provided by personal mobile devices, leading to inefficiencies and increased resource usage and costs.
Innovation Solution
A method and system that obtain application-usage data from personal mobile devices and compare it with vehicle feature usage data to determine a usage preference, allowing for the identification and potential removal of redundant vehicle features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If vehicles are equipped with redundant features to duplicate mobile device functionalities, then user experience and functionality are improved, but resource consumption and costs increase
Solution Approach 1:
The patent extracts the redundant vehicle features that duplicate mobile device functionalities by comparing usage data from both sources. When a vehicle feature is found to be redundant (i.e., the mobile device application is used more frequently), the system removes or deactivates that vehicle feature, thereby reducing resource consumption while maintaining necessary functionality.
Solution Approach 2:
The system discards unused vehicle features by identifying them through usage comparison and removing them from active operation. This allows the vehicle system to recover resources (computing power, memory, energy) that were previously consumed by these redundant features, while the capability is recovered through the operator's personal mobile device.
2Adaptability or versatility
If vehicles are equipped with redundant features to duplicate mobile device functionalities, then user experience and functionality are improved, but manufacturing costs and system complexity increase
Solution Approach 1:
The patent extracts the redundant vehicle features that duplicate mobile device functionalities by comparing usage data from both sources. When a vehicle feature is found to be redundant (i.e., the mobile device application is used more frequently), the system removes or deactivates that vehicle feature, thereby reducing resource consumption while maintaining necessary functionality.
Solution Approach 2:
The system discards unused vehicle features by identifying them through usage comparison and removing them from active operation. This allows the vehicle system to recover resources (computing power, memory, energy) that were previously consumed by these redundant features, while the capability is recovered through the operator's personal mobile device.
3Loss of substance
If usage data is collected and analyzed from personal mobile devices and vehicle features, then redundant features can be identified and removed, but data processing complexity increases
Solution Approach 1:
The system performs preliminary actions by collecting and storing usage data from both vehicle features and personal mobile devices before making removal decisions. This preliminary data collection and analysis phase allows the system to identify usage patterns and determine redundancy beforehand, making the actual feature removal process more efficient and less complex.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring usage data from both vehicle features and personal mobile devices. This feedback loop allows the system to dynamically identify when a vehicle feature has become redundant based on actual usage patterns, enabling data-driven decisions about feature removal while adapting to changing user behaviors.
Data Source
AI summary
An embodiment takes the form of a system that obtains application-usage data from a personal mobile device of a vehicle operator of a vehicle. The application-usage data reflects a usage, during operation of the vehicle, of an application on the personal mobile device. The system identifies a vehicle feature, of the vehicle, that provides a vehicle functionality similar to an application functionality provided by the application on the personal mobile device, and performs a comparison of the obtained application-usage data with feature-usage data. The feature-usage data reflects a usage, during operation of the vehicle, of the identified vehicle feature. The system determines, based on the comparison, a usage preference for the application during operation of the vehicle over the identified vehicle feature.


